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Reproducible Evaluation of System Efficiency with a Model of Architecture: From Theory to Practice

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Details

Original languageEnglish
Pages (from-to)2050-2063
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume37
Issue number10
Early online date16 Nov 2017
DOIs
Publication statusPublished - Oct 2018
Publication typeA1 Journal article-refereed

Abstract

Current trends in high performance and embedded computing include design of increasingly complex hardware architectures with high parallelism, heterogeneous processing elements and non-uniform communication resources. In order to take hardware and software design decisions, early evaluations of the system non-functional properties are needed. These evaluations of system efficiency require Electronic System-Level (ESL) information on both the algorithms and the architecture. Contrary to algorithm models for which a major body of work has been conducted on defining formal Models of Computation (MoCs), architecture models from the literature are mostly empirical models from which reproducible experimentation requires the accompanying software. In this paper, a precise definition of a Model of Architecture (MoA) is proposed that focuses on reproducibility and abstraction and removes the overlap previously existing between the notions of MoA and MoC. A first MoA, called the Linear System-Level Architecture Model (LSLA), is presented. To demonstrate the generic nature of the proposed new architecture modeling concepts, we show that the LSLA Model can be integrated flexibly with different MoCs. LSLA is then used to model the energy consumption of a State-of-the-Art Multiprocessor System-on-Chip (MPSoC) when running an application described using the Synchronous Dataflow (SDF) MoC. A method to automatically learn LSLA model parameters from platform measurements is introduced. Despite the high complexity of the underlying hardware and software, a simple LSLA model is demonstrated to estimate the energy consumption of the MPSoC with a fidelity of 86%.

Keywords

  • Algorithm design and analysis, architecture, Complexity theory, Computational modeling, Computer architecture, design space exploration, Energy consumption, Hardware, hardware/software co-design, modeling, multiprocessor SoC, performance optimization, Ports (Computers), power modeling and estimation., system on chip

Publication forum classification

Field of science, Statistics Finland